A New Pipeline for the Normalization and Pooling of Metabolomics Data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists

Response to comment on “Indoor terrestrial gamma dose rate mapping in France: A case study using two different geostatistical models” by Warnery et al.

International audienceElements to answer the points raised in the Letter in question are proposed, notably about exposure metrics and their influence on the results and statistical power of epidemiological studies. © 201

Developmental and pathogen-induced activation of an msr gene, str246C, from tobacco involves multiple regulatory elements

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ISOLATION OF FUCANOLYTIC MARINE BACTERIA AS A SOURCE OF FUCAN DEPOLYMERAZING ENZYMES. - APPLICATION TO THE INDUSTRIAL PRODUCTION OF BIOLOGICALLY-ACTIVE OLIGO-FUCANS

Conférence du 26 au 31 Mars 2007. Communication Orale

ISOLATION OF FUCANOLYTIC MARINE BACTERIA AS A SOURCE OF FUCAN DEPOLYMERAZING ENZYMES. - APPLICATION TO THE INDUSTRIAL PRODUCTION OF BIOLOGICALLY-ACTIVE OLIGO-FUCANS

Conférence du 26 au 31 Mars 2007. Communication Orale